UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
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TL;DR - UnifiedPlayers jointly trains task planning, tool-based execution, and verifier generation as cooperating reinforcement-learning players. This coordination improves reasoning performance while producing more adaptive and discriminative evaluation signals.
- Uses specialized Planning, Execution, and Evaluation Players coordinated through role-specific rewards under GRPO.
- Generates tasks, multi-turn trajectories with Python tool calls, and executable verifiers within one self-evolving framework.
- Outperforms the strongest prior baseline by at least 3.5% on mathematical reasoning and 3.9% on general reasoning across two model backbones and 12 benchmarks.
- The learned verifier reaches 84.2% adversarial detection accuracy and yields 2.03Ă— higher per-question reward variance than self-consistency.
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UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
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TL;DR - UnifiedPlayers jointly trains task planning, tool-based execution, and verifier generation as cooperating reinforcement-learning players. This coordination improves reasoning performance while producing more adaptive and discriminative evaluation signals.
- Uses specialized Planning, Execution, and Evaluation Players coordinated through role-specific rewards under GRPO.
- Generates tasks, multi-turn trajectories with Python tool calls, and executable verifiers within one self-evolving framework.
- Outperforms the strongest prior baseline by at least 3.5% on mathematical reasoning and 3.9% on general reasoning across two model backbones and 12 benchmarks.
- The learned verifier reaches 84.2% adversarial detection accuracy and yields 2.03Ă— higher per-question reward variance than self-consistency.